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首页> 外文期刊>International journal of digital crime and forensics >A Privacy Protection Approach Based on Android Application's Runtime Behavior Monitor and Control
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A Privacy Protection Approach Based on Android Application's Runtime Behavior Monitor and Control

机译：基于Android应用程序运行时行为监控的隐私保护方法

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摘要

This article proposes a system that focuses on Android application runtime behavior forensics. Using Linux processes, a dynamic injection and a Java function hook technology, the system is able to manipulate the runtime behavior of applications without modifying the Android framework and the application's source code. Based on this method, a privacy data protection policy that reflects users' intentions is proposed by extracting and recording the privacy data usage in applications. Moreover, an optimized random forest algorithm is proposed to reduce the policy training time. The result shows that the system realizes the functions of application runtime behavior monitor and control. An experiment on 134 widely used applications shows that the basic privacy policy could satisfy the majority of users' privacy intentions.
机译：本文提出了一个针对Android应用程序运行时行为取证的系统。使用Linux进程，动态注入和Java函数挂钩技术，该系统无需修改Android框架和应用程序的源代码即可操纵应用程序的运行时行为。基于此方法，通过提取和记录应用程序中的隐私数据使用情况，提出了一种反映用户意图的隐私数据保护策略。此外，提出了一种优化的随机森林算法来减少策略训练时间。结果表明，该系统实现了应用程序运行时行为的监视和控制功能。对134种广泛使用的应用程序进行的实验表明，基本隐私策略可以满足大多数用户的隐私意图。

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  • 作者

    Feng Liu; Fan Wu; Ran Sun; Wenhao Fan; YuanAn Liu; Hui Lu;

  • 作者单位

    State Key Laboratory of Information Security, Institute of Information Engineering and School of Cybersecurity University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China;

    Beijing University of Posts and Telecommunications, Beijing, China;

    Beijing University of Posts and Telecommunications, Beijing, China;

    Beijing University of Posts and Telecommunications, Beijing, China;

    Beijing University of Posts and Telecommunications, Beijing, China;

    Guangzhou University, Guangzhou, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Android Privacy; Forensics Method; Machine Learning; Process Injection;

    机译：Android隐私;取证方法;机器学习;过程注入;

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